Abstract: Disclosed herein are methods, systems, and processes for distributed logging for securing non-repudiable transactions. Credentials, request information, response information, and action items generated and received by a requesting computing system and a responding computing system, and transmitted between the requesting computing system and the responding computing system are separately recorded and stored in a requestor log maintained by the requesting computing system and in a responder log maintained by the responding computing system.

Abstract: Disclosed herein are methods, systems, and processes for distributed logging for securing non-repudiable transactions. Credentials, request information, response information, and action items generated and received by a requesting computing system and a responding computing system, and transmitted between the requesting computing system and the responding computing system are separately recorded and stored in a requestor log maintained by the requesting computing system and in a responder log maintained by the responding computing system.

Abstract: Provided is process, including: obtaining interaction-event records; determining, based on at least some of the interaction-event records, sets of event-risk scores, wherein: at least some respective event-risk scores are indicative of an effective of a respective risk ascribed by a first entity to a respective aspect of a second entity; and at least some respective event-risk scores are based on both: respective contributions of respective corresponding events to a subsequent event, and a risk ascribed to a subsequent event; and storing the sets of event-risk scores in memory.

Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.

Abstract: In some implementations, a computing device may determine, from multiple data sources, multiple event timelines, with each event timeline associated with a customer. Each event in an event timeline represents an interaction between the customer and a vendor of goods and/or services. For N (N>1) marketing campaigns, N augmented timelines may be created for each timeline by augmenting each event timeline with the individual marketing campaigns. Thus, for M (M>1) customers, M×N augmented event timelines may be created. A trained machine learning model may perform an analysis of each augmented event timeline to predict results of executing each marketing campaign. The results may include total predicted revenue and total predicted cost resulting from executing each marketing campaign. A particular marketing campaign from the N marketing campaigns may be selected and execution of one or more marketing events may be initiated.

Abstract: In some implementations, a computing device determines an event timeline that comprises one or more finance-related events associated with a person. A production classifier may be used to determine (i) an individual contribution of each event in the event timeline to a financial capacity of the person and (ii) a first decision regarding whether to extend credit to the person. A bias monitoring classifier may, based on the event timeline, determine a second decision whether to extend credit to the person. The bias monitoring classifier may be trained using pseudo-unbiased data. If a difference between the first decision and the second decision satisfies a threshold, the production classifier may be modified to reduce bias in decisions made by the production classifier.

Abstract: In some implementations, an event timeline that includes one or more interactions between a customer and a supplier may be determined. A starting value may be assigned to individual events in the event timeline. A sub-sequence comprising a portion of the event timeline that includes at least one reference event may be selected. A classifier may be used to determine a previous relative value for a previous event that occurred before the reference event and to determine a next relative value for a next event that occurred after the reference event until all events in the event timeline have been processed. The events in the event timeline may be traversed and a monetized value index assigned to individual events in the event timeline.

Abstract: Systems and methods are described to identify in the images text, people, landmarks, objects, or any combination thereof and to store and search for images based on extracted data. A portable computing device, such as a wireless phone or tablet computer, may capture an image, determine context data associated with the image, and send the image and context data to an analyzer. The analyzer may extract data from the image and send the extracted data to the portable computing device. For example, the analyzer may determine if the image includes alphanumeric characters and perform character recognition (e.g., using optical character recognition (OCR) or similar technology). A format of the characters that are recognized in the image may be analyzed to determine additional information, such as whether the characters are a phone number, a uniform resource locator (URL), a name of a person, a name of a location, or the like. The analyzer may determine if the image includes a person, a landmark, an object, etc.

Abstract: Systems and techniques for determining an expertise of an employee in an enterprise are described. A crawler may examine one or more external data sources that are external to an enterprise network associated with the enterprise to identify one or more documents associated with the employee. The external data sources may include patent databases, technical paper databases, and the like. A classifier may be used to determine keywords in the one or more documents. For each of the keywords, a term frequency-inverse document frequency (TF-IDF) value may be determined. The keywords may be ranked based at least in part on the TF-IDF value associated with each keyword to create ranked keywords. The ranked keywords may be displayed. A font characteristic used to display a particular keyword of the ranked keywords may be determined based at least partly on the TF-IDF value associated with the particular keyword.

Abstract: Systems and methods are described to identify in the images text, people, landmarks, objects, or any combination thereof and to store and search for images based on extracted data. A portable computing device, such as a wireless phone or tablet computer, may capture an image, determine context data associated with the image, and send the image and context data to an analyzer. The analyzer may extract data from the image and send the extracted data to the portable computing device. For example, the analyzer may determine if the image includes alphanumeric characters and perform character recognition (e.g., using optical character recognition (OCR) or similar technology). A format of the characters that are recognized in the image may be analyzed to determine additional information, such as whether the characters are a phone number, a uniform resource locator (URL), a name of a person, a name of a location, or the like. The analyzer may determine if the image includes a person, a landmark, an object, etc.

Abstract: Methods for preventing the transmission of sensitive information to locations outside of a secure network by a person who has legitimate access to the sensitive information are described. In some embodiments, in order for an end user of a computing device to establish a secure connection with a secure network and access data stored on the secure network, a client application running on the computing device may be required by the secure network. The client application may monitor visual cues (e.g., facial expressions and gestures) associated with the end user, detect suspicious activity performed by the end user based on the visual cues, and in response to detecting suspicious activity may perform mitigating actions to prevent the transmission of sensitive information such as alerting human resources personnel or requiring authorization prior to sending information to locations outside of the secure network.

Abstract: Systems and techniques to reduce bandwidth usage of video frames in a videoconferencing system are described. A computing device may receive a first frame of a first video stream from an imaging device and decompose the frame into a plurality of portions. The computing device may select a first portion of the plurality of portions, determine that the first portion matches a sent portion in a sent catalog, determine a first identifier associated with the first portion, and send the first identifier to a server. The computing device may select a second portion of the plurality of portions, determine that the second portion fails to match any of the sent portions in the sent catalog, create and associate a second identifier with the second portion, store the second portion with the second identifier in the sent catalog, and send the second portion to the server.

Abstract: Systems and techniques to dynamically correct a gaze of participants in a video conference are described. A computing device participating in a video conference may determine that a frame of a video stream includes features of a face, extract a portion of the frame that includes a first pair of eyes, and determine that the first pair of eyes are looking in a non-forward direction. The computing device may retrieve, from a database, a stored portion that includes a second pair of eyes that are looking in a forward direction, and modify the frame by substituting the stored portion for the portion in the frame to create a modified frame. The computing device may send the modified frame to a videoconferencing server for distribution to other computing devices participating in the video conference.

Abstract: Methods for preventing the transmission of sensitive information to locations outside of a secure network by a person who has legitimate access to the sensitive information are described. In some embodiments, in order for an end user of a computing device to establish a secure connection with a secure network and access data stored on the secure network, a client application running on the computing device may be required by the secure network. The client application may monitor visual cues (e.g., facial expressions and gestures) associated with the end user, detect suspicious activity performed by the end user based on the visual cues, and in response to detecting suspicious activity may perform mitigating actions to prevent the transmission of sensitive information such as alerting human resources personnel or requiring authorization prior to sending information to locations outside of the secure network.

Abstract: Methods for preventing the transmission of sensitive information to locations outside of a secure network by a person who has legitimate access to the sensitive information are described. In some embodiments, in order for an end user of a computing device to establish a secure connection with a secure network and access data stored on the secure network, a client application running on the computing device may be required by the secure network. The client application may monitor visual cues (e.g., facial expressions and gestures) associated with the end user, detect suspicious activity performed by the end user based on the visual cues, and in response to detecting suspicious activity may perform mitigating actions to prevent the transmission of sensitive information such as alerting human resources personnel or requiring authorization prior to sending information to locations outside of the secure network.

Abstract: A management server in a communications network receives information for display at a plurality of user devices. The information includes multiple user interface components for display on the user devices. Upon receiving the information, the management server identifies the different components and selectively distributes the components to different ones of the user devices based on predefined routing data stored in a memory accessible to the management server.

Abstract: Methods for providing feedback information regarding a person's focus of attention during a live video communication are described. The live video communication may comprise a live video conference. The feedback information may correspond with non-verbal cues such as who a speaking person is looking at when they are speaking and whether a listener is paying attention to the speaking person. In some embodiments, a dominant speaker in a live video conference may be determined and a live video stream that is being viewed by the dominant speaker may be identified. An identification of the live video stream may be transmitted to computing devices associated with other participants in the live video conference. Images associated with the live video stream being displayed to the other participants may be highlighted, enlarged, or moved to a different location on displays used by the other participants.

Abstract: Methods for preventing the transmission of sensitive information to locations outside of a secure network by a person who has legitimate access to the sensitive information are described. In some embodiments, in order for an end user of a computing device to establish a secure connection with a secure network and access data stored on the secure network, a client application running on the computing device may be required by the secure network. The client application may monitor visual cues (e.g., facial expressions and gestures) associated with the end user, detect suspicious activity performed by the end user based on the visual cues, and in response to detecting suspicious activity may perform mitigating actions to prevent the transmission of sensitive information such as alerting human resources personnel or requiring authorization prior to sending information to locations outside of the secure network.

Abstract: Methods for preventing the transmission of sensitive information to locations outside of a secure network by a person who has legitimate access to the sensitive information are described. In some embodiments, in order for an end user of a computing device to establish a secure connection with a secure network and access data stored on the secure network, a client application running on the computing device may be required by the secure network. The client application may monitor visual cues (e.g., facial expressions and gestures) associated with the end user, detect suspicious activity performed by the end user based on the visual cues, and in response to detecting suspicious activity may perform mitigating actions to prevent the transmission of sensitive information such as alerting human resources personnel or requiring authorization prior to sending information to locations outside of the secure network.

Abstract: Methods for providing feedback information regarding a person's focus of attention during a live video communication are described. The live video communication may comprise a live video conference. The feedback information may correspond with non-verbal cues such as who a speaking person is looking at when they are speaking and whether a listener is paying attention to the speaking person. In some embodiments, a dominant speaker in a live video conference may be determined and a live video stream that is being viewed by the dominant speaker may be identified. An identification of the live video stream may be transmitted to computing devices associated with other participants in the live video conference. Images associated with the live video stream being displayed to the other participants may be highlighted, enlarged, or moved to a different location on displays used by the other participants.